3 Types of Data Swamping and How to Avoid It

first_imgThe influx of IoT technology provides tons of benefits when implemented the right way, but the reality is it can be tough for companies to make the best decisions regarding the data volume and complexity. The vast number of sensors, embedded systems and connected devices making their way on to the edge of the network continues to grow. While everyone wants to tap the rich potential of IoT data, we’ve seen that the data flowing through so-called network tributaries can quickly overload traditional data lakes and analysis tools, leading to data swamping.Data swamping is an expensive state resulting from the inefficient handling of information within an organization. In fact, it is estimated that today nearly 99 percent of all collected data is never utilized. The results of data swamping are slow decisions and a costly network and storage burden. Data swamping can present itself in several interrelated ways:1. Long looping: The goal of IoT is to make valuable, data-based decisions in a timely fashion.  Despite the fast-moving requirements of modern organizations, some still backhaul all collected data directly to their on premise data center (or cloud) for analytics, only to push decisions all the way back to the collection points at the edge.  This is highly inefficient when shorter-term decisions are possible and perhaps even required. Unfortunately, the concept of an immediate cloud-based decision is contradictory and doesn’t work in use cases where periods of lost connectively will disrupt critical operations. Robust IoT Gateways, like the Dell Edge Gateway 5000 Series, can run in-memory analytics on streams of incoming data to help companies make rapid decisions near the very edge of the network, while routing meaningful data to the right final repository for further action or longer term storage.2. Data hoarding:  IoT data is often perishable and of little long-term value (think of binary automated building data that the lights are on or off).  Aside from the immediate need to execute on rules against a given context, a significant amount of IoT data is of low-level importance and can be discarded on the spot. Many organizations are not only sending this data long distances for decision making, they are storing it without any clear vision for its future use.  This transfer and hoard-like storage behavior results in complexity and data silos, which contributes to the data swamp.  Another benefit of running local stream analytics at the edge is the ability to apply metadata at the point of ingestion that can help ensure proper routing to a final repository and facilitate future access.3. Traffic density: Sending data long distances through networks can not only present missed decision-making opportunities, but also results in expensive provisioning, transfer and storage costs. This behavior can be likened to constantly overnighting packages of junk to yourself only to stack them up in an expensive storage unit with no intended use.  The expenses add up especially when dealing with wide-area networks, like cellular, and high-bandwidth data such as video.  Rather than sending live streams over the network it is more efficient to analyze data locally and only send small bits of information representing meaningful events – for example, the detection of motion in a secure area or notification of an impending failure in remote equipment. The ideal solution is to make decisions as close as possible to where action is taking place so network cost is only incurred for centralizing data that will be truly useful in the future.&nbsp;</p><p>As the processing power of edge gateways has increased, these devices have become more than mere entry points for sensor data.  Gateways now possess the ability to make rapid decisions at the edge of the network and immediately upstream of sensors. By acting like a data “spam filter,” gateways can help organizations rapidly act on perishable insights, dispatch useless data on the spot and route meaningful data to central repositories for further analysis. One analogy I like to use for the value of in-the-moment edge analytics is the notion of picking up after yourself on a daily basis. By putting your keys, mail, groceries, etc. away right when you get home, your house stays clean, but if you just dump everything on the floor upon coming in the house, you quickly end up with an insurmountable mess!Dell’s new edge IoT gateways, combined with distributed analytics capabilities powered by Dell Statistica, and assets from our ISV partners are bringing analytics closer to data sources. Compared to many competitor products that require a failure-prone fan to operate at full processing capacity in harsh industrial conditions, Dell’s gateways are designed to perform at their maximum potential at specified temperature extremes with zero airflow. This means organizations can deploy Dell gateways virtually anywhere to capitalize on the benefits of cloud computing combined with powerful edge analytics.  This can prevent the dreaded data swamp and provide faster and more secure business insights while saving on the costly transfer of data to and from the cloud.Swamp image via Creative Commons by shankar s.last_img read more

AVIC Orders Ten Bulkers from Dalian Shipbuilding

first_imgAVIC International Leasing and SDTR Marine have signed an agreement for the construction of ten bulk carriers at China’s Dalian Shipbuilding Industry.Under the deal, signed on January 15, the Kamsarmaxes are scheduled to start joining their owner in 2021.The parties did not unveil the price tag of the new eco bulkers, which would feature 85,000 dwt.The deal represents the first shipbuilding contract in Dalian Shipbuilding Industry’s 2019 orderbook.On January 15, the shipbuilder also delivered a new 85,000 cbm very large ethane carrier (VLEC) and held a steel cutting ceremony for a second VLEC, which would feature a length of 231.6 meters and a width of 36.6 meters.World Maritime News Stafflast_img read more

Badgers face rival UMD

first_imgGREGORY DIXON/Herald photoLast weekend, the No. 4 Wisconsin women’s hockey team facedthe last-place team in the WCHA, Bemidji State. This weekend, the Badgers(10-4-2, 6-2-2 WCHA) will face a much stiffer test when No. 3 Minnesota-Duluth(10-3-1, 9-3-0 WCHA), the top team in the conference, comes to the Kohl Centerfor a weekend series.UW and UMD have developed a fierce rivalry over the past fewyears. The Badgers played the Bulldogs five times last season, going 3-1-1,including a win over UMD in the NCAA Championship game.”They know that we are a good team, and we know that theyare a good team,” senior Emily Morris said. “We each spend all week preparingfor one another, and we are each going to bring our ‘A’ game for each other.Who wants it more is the team that is going to win.”Adding to the intensity of the matchup is the fact that UMDsits atop the WCHA standings. The Bulldogs have 18 points in the conference,while the Badgers are in third place with 14 points. If UW sweeps UMD, the twoteams would be in a tie for first place.”Obviously, playing against the top-seeded team, we willhave a lot of motivation and drive this weekend,” junior Erika Lawler said.”Since they are the top-seeded team, I think that we will feel some pressure,not in a fearful way, but in a positive way. Because we are not the first placeteam, it encourages us to work hard and earn that spot.”Minnesota-Duluth comes into the series as the No. 1offensive team in the WCHA, averaging 4 goals per game. Wisconsin, however, isthe No. 1 defensive team in the WCHA, giving up an average of 1.1 goals pergame.”It starts in the net with our goaltender and her ability tokeep the puck out of the net,” head coach Mark Johnson said of his team’ssuccess on defense. “If we are going to be successful … our margin of errorisn’t real high right now because we are not putting the puck in the net. Weneed our defense to help us win some games when we are not scoringconsistently.”The Bulldogs have one of the top goaltenders in theconference in sophomore Kim Martin. Martin is second in the WCHA in goalsallowed at 1.46 a game and is first in save percentage at .952. Martin couldprove to be a tough challenge for a team that has struggled to score goalsconsistently this season.Last weekend, Wisconsin scored seven goals in Friday’s gameagainst Bemidji State, including three power play goals en route to a 7-0 win.Saturday, however, proved to be a challenge for UW, as they couldn’t manage agoal in a 0-0 tie.”It is frustrating that we were unable to put the puck inthe net,” Lawler said. “You just have to take it in stride and work on scoringin practice. Hopefully we can learn from that game, and the next time we runinto a really hot goaltender we will find a way to put the puck in the net.”In hopes of bolstering their offense, the Badgers have madetheir power play a point of emphasis in practice the past few weeks.”We have practiced the power play a lot,” Lawler said. “Itis all about moving the puck faster and being confident, and I think that wewill have more success with our power play.”last_img read more